摘 要随着计算机和网络技术的迅速发展，信息安全显示出前所未有的重要性，而安全、方便的个人身份鉴别技术作为信息安全的一个重要方面越来越受到人们的重视。虽然利用掌纹进行个人身份鉴别已经引起了许多研究者的重视，但是，对安全、有效的掌纹识别技术的研究仍然是一个充满挑战性的问题。本学位论文通过对掌纹图像的去噪、掌纹图像的定位和归一化、掌纹特征的提取和匹配等方法的研究，提出了一系列的掌纹分析方法。本学位论文首先提出了一种新的掌纹图像去噪算法—布特沃斯-小波去噪算法，并通过实验与低通滤波、邻域平均滤波以及Multithr shrink去噪算法进行了比较，从而验证了该去噪算法的有效性。其次，利用LOG算子和8-邻域边界跟踪相结合的方法提取出手掌轮廓线以及轮廓线的方向链码，通过分析角点位置处方向链码所具有的规律性，提出了一种快速的手掌轮廓线的角点检测方法。第三，根据提取出的角点对掌纹图像进行定位，并对感兴趣区域（ROI）进行切取，提出了根据手掌的大小切取ROI的方法。第四，通过分析局部小波能量特征和全局小波能量特征的匹配能力，提出将局部小波能量特征和全局小波能量特征进行特征融合之后作为掌纹特征进行匹配的观点。最后，通过实验验证了这一系列掌纹分析方法的有效性。

ABSTRACT With the rapid development of computer and Internet technology all over the world, information security has become more important than before. As an important aspect of information security, the reliable and convenient identity recognition technology has invoked increasing interest. Although using palmprint for personal recognition has drawn interests from researchers, it is still a challenging topic. By studying the denoising algorithms, location and normalization methods, feature extraction and matching methods of palmprint image, this dissertation brings forward a series of methods for palmprint analysis. Firstly, a novel palmprint image denoising algorithm–Butterworth-wavelet denoising algorithm is proposed in this dissertation, and it is compared with lowpass filter denoising algorithm, neighborhood average denoising algorithm and Multithr shrink denoising algorithm by experiment. The experiment results prove the validity of this denoising algorithm. Secondly, the methods of LOG operator and 8-neighborhood boundary-tracking algorithm is used to extract palm contour and its chain-code. By analyzing the regularity of chain-code of palm contour, a new and rapid corner-detection method is proposed. Thirdly, the palmprint image is located and the ROI (Region Of Interest) is extracted according to the contour corner. Simultaneously, a ROI extraction method according to the proportion of palm size is put forward. Fourthly, through analyzing the matching capacity of both local wavelet energy feature and global wavelet energy feature, the feature fusion method is proposed .Finally, the validity of palmprint analysis methods proposed in this dissertation is testified by experiments.